The measurement of serum prostate specific antigen (PSA) is widely used for the screening and early detection of prostate cancer (PCa). As discussed in the public report “Polygenic Risk Score Improves Prostate Cancer Risk Prediction: Results from the Stockholm-1 Cohort Study” by Markus Aly and co-authors as published in EUROPEAN UROLOGY 6 0 (2011) 21-28 (which is incorporated by reference herein), serum PSA that is measurable by current clinical immunoassays exists primarily as either the free “non-complexed” form (free PSA), or as a complex with a-lantichymotrypsin (ACT). The ratio of free to total PSA in serum has been demonstrated to significantly improve the detection of PCa. Other factors, like age and documented family history may also improve the detection of PCa further. The measurement of genetic markers related to PCa, in particular single nucleotide polymorphisms (SNP), is an emerging modality for the screening and early detection of prostate cancer. Analysis of multiple PCa related SNPs can, in combination with biomarkers like PSA and with general information about the patient improve the risk assessment through a combination of several SNPs into a genetic score.
Attempts to combine information from multiple sources into one algorithmic model have been disclosed in the past for the prediction of a different end-point, PCa risk, as compared to the present invention. In the public report “Blood Biomarker Levels to Aid Discovery of Cancer-Related Single-Nucleotide Polymorphisms: Kallikreins and Prostate Cancer” by Robert Klein and co-authors as published in Cancer Prev Res (2010), 3(5):611-619 (which is incorporated by reference herein), the authors discuss how blood biomarkers can aid the discovery of novel SNP, but also suggest that there is a potential role for incorporating both genotype and marker levels in predictive models for the estimation of PCa risk. Furthermore, this report provides evidence that the non-additive combination of genetic markers and biomarkers in concert may have predictive value for the estimation of PCa risk. Later, Xu and co-inventors disclosed a method for assessing the risk of a subject having PCa in the patent application WO2012/031207A2, which is incorporated by reference herein. This disclosure describes a method to predict if an individual is at risk of having prostate cancer through the use of genetic information in 33 defined SNP, which implicitly can be used for the prediction of if the tested individual is suitable for chemopreventive therapy. Chemopreventive therapy is proactive medication supplied prior to cancer diagnosis, with the purpose of reducing the likelihood of cancer onset.
Even though PSA is predominantly used for diagnosis of PCa, it has also been described as a prognostic marker for individuals that are diagnosed with PCa. One possible method for estimating the prognosis of PCa in an individual is to follow the progression of the PSA value, as described by Collette and co-authors in the public report “Prostate specific antigen: a prognostic marker of survival in good prognosis metastatic prostate cancer?” as published in Eur Urol. 2003 August; 44(2):182-9; discussion 189 (which is incorporated by reference herein).
There are further other markers suitable for assessing the prognosis of a PCa diagnosis, as described by EP Gelmann and SM Henshall in the public report “Clinically Relevant Prognostic Markers for Prostate Cancer: The Search Goes On” as published in Ann Intern Med. 5 May 2009; 150(9):647-649 (which is incorporated by reference herein). In this report, the histologic grade (Gleason score), P53 expression, BCL2 expression and microvessel density are discussed as potential prognostic markers, even though they all have major shortcomings for that purpose.
The current clinical practice (in Sweden) is to use the Gleason score as one major input for decision on if to engage in active treatment (surgery or radiation therapy) for prostate cancer that is confined to the prostate gland. Other factors, like age, unrelated diseases, estimated tumor extent, and the opinion of the patient are also important for this decision. As a rule of thumb, the vast majority of patients with Gleason 8+ tumors are treated in an active manner. For patients with Gleason 6 tumors, a smaller fraction are treated in an active manner, but most are left with active surveillance. It is acknowledged that since the patient has impact in this decision process, the decision is of a subjective nature. A prognostic method in the field of deciding whether to treat a patient in an active manner would be most beneficial if decision support is provided for the borderline cases, i.e. for patients with Gleason 6-7 tumors.
Hence, the estimation of prognosis is a difficult task where improvements in current state-of-the-art would lead to great savings in the society. Of particular importance is to estimate if an individual diagnosed with PCa will require advanced therapy (surgery or radiation) or if the disease will be monitored by active surveillance. Advanced therapy has a number of serious side-effects, including impotence (predominantly for surgery), incontinence and gastrointestinal issues (the two latter predominantly for radiation therapy). This invention provides, however, predictive models for the prognosis of PCa through analysis of biomarkers and genetic profile of the individual diagnosed with PCa.